Abstract: A method of determining at least one of position and attitude in relation to an object is provided. The method includes capturing at least two images of the object with at least one camera. Each image is captured at a different position in relation to the object. The images are converted to edge images. The edge images of the object are converted into three-dimensional edge images of the object using positions of where the at least two images were captured. Overlap edge pixels in the at least two three-dimensional edge images are located to identify overlap points. A three dimensional edge candidate point image of the identified overlapped points in an evidence grid is built. The three dimensional candidate edge image in the evidence grid is compared with a model of the object to determine at least one of a then current position and attitude in relation to the object.

Abstract: A method of generating a map for image aided navigation comprises detecting one or more edges in one or more terrain images, and obtaining a compressed edge representation of the one or more edges. The compressed edge representation is obtained by a method comprising fitting a geometric form or other mathematical model to the one or more edges, calculating one or more coefficients based on the fitted geometric form or other mathematical model, and storing the one or more coefficients in a database for use in generating the map for image aided navigation.

Abstract: A method of mitigating filter inconsistency of a heading estimate in an inertial navigation system is provided.

Abstract: Systems and methods for inertial reference system alignment are provided. In certain embodiments, a system comprises an inertial reference system, the inertial reference system providing motion measurements; and a processing system coupled to receive the motion measurements from the inertial reference system. Further, the processing system is configured to execute instructions that direct the processing system to identify one or more frequencies in the spectrum of the motion measurements that are associated with vibrations; attenuate the motion measurements at the one or more frequencies; and use the attenuated measurements to aid in the production of navigation information.

Abstract: A method of mitigating filter inconsistency of a heading estimate in an inertial navigation system is provided.

Abstract: In one embodiment, a method for tracking multiple objects with a probabilistic hypothesis density filter is provided. The method includes comparing second track IDs corresponding to newly obtained measurements to one or more first track IDs corresponding to a Tk+1 predicted intensity having a predicted weight. If all of the one or more first track IDs match any of the second track IDs, the predicted weight is multiplied by a first value. If less than all of the one or more first track IDs match any of the second track IDs, the predicted weight is multiplied by a second value, wherein the second value is greater than the first value. The method then determines whether to prune the Tk+1 predicted intensity based on the predicted weight after multiplying with either the first value or the second value.

Abstract: A method of mitigating filter inconsistency of a heading estimate in an inertial navigation system is provided.

Abstract: Systems and methods for off-line and on-line sensor calibration are provided. In certain embodiments, a method for calibrating a sensor comprises receiving at least one reference measurement describing a system state for a system; and receiving at least one sensor measurement from the sensor, wherein the at least one sensor measurement is acquired from an observation of the environment of the system by the sensor. The method also comprises calculating a model residual power spectral density based on the at least one reference measurement and a sensor measurement model; and calculating a measurement residual power spectral density based on the at least one sensor measurement and the at least one reference measurement. Further, the method comprises identifying sensor parameters that morph the model residual power spectral density towards the measurement residual power spectral density.

Abstract: A system and method of generating a landing trajectory for use in landing an aircraft onto a deck of a waterborne ship includes sensing motion of the ship, and sensing wind speed and wind direction. The sensed motion of the ship is processed to generate estimates of ship attitude and vertical speed, and the sensed wind speed and wind direction are processed to generate estimates of air-wake disturbances ahead of the aircraft. The landing trajectory is generated based on the estimates of ship attitude and vertical speed and the estimates of air-wake disturbances. The system and method implement model predictive control to calculate the control maneuvers multiple steps ahead, which provides the capability to smoothly control the timing of the aircraft touchdown phase.

Abstract: A method to filter outliers in an image-aided motion-estimation system is provided. The method includes selecting eight-image-points in a first image received from a moving imaging device at at least one processor; selecting eight-image-points in a second image that correspond to the selected eight-image-points in the first image at the at least one processor, the second image being received from the moving imaging device; scaling the selected image-points at the at least one processor so the components of the selected image-points are between two selected values on the order magnitude of 1; building an 8-by-9 matrix (A) from the scaled selected image-points at the at least one processor; determining a condition number for the 8-by-9 matrix at the at least one processor; and rejecting the 8-by-9 matrix built from the selected image-points when the determined condition number is greater than or equal to a condition-number threshold.

Abstract: In one embodiment, a method for tracking multiple objects with a probabilistic hypothesis density filter is provided. The method includes comparing second track IDs corresponding to newly obtained measurements to one or more first track IDs corresponding to a Tk+1 predicted intensity having a predicted weight. If all of the one or more first track IDs match any of the second track IDs, the predicted weight is multiplied by a first value. If less than all of the one or more first track IDs match any of the second track IDs, the predicted weight is multiplied by a second value, wherein the second value is greater than the first value. The method then determines whether to prune the Tk+1 predicted intensity based on the predicted weight after multiplying with either the first value or the second value.

Abstract: In one embodiment, a method of tracking multiple objects with a probabilistic hypothesis density filter is provided. The method includes providing a plurality of intensities. The plurality of intensities are pruned based on their respective weight to remove lower weighted intensities and produce a first set of intensities. Intensities in the first set of intensities that are identified as corresponding to the same object are then merged to produce a second set of intensities. The second set of intensities is then pruned again to produce a final set of intensities, wherein pruning the second set of intensities includes in the final set of intensities, up to a threshold number of intensities having the largest weights in the second set of intensities and excludes from the final set of intensities any remaining intensities in the second set of intensities.

Abstract: In one embodiment, a method of tracking multiple objects with a probabilistic hypothesis density filter is provided. The method includes generating a first intensity by combining a first one or more measurements, wherein a first set of track IDs associated with the first intensity includes track IDs corresponding to respective measurements in the first one or more measurements. A second intensity is generated by combining a second one or more measurements, wherein a second set of track IDs associated with the second intensity includes track IDs corresponding to respective measurements in the second one or more measurements. The first set of track IDs is compared to the second set of track IDs, and the first intensity is selectively merged with the second intensity based on whether any track IDs in the first set of track IDs match any track IDs in the second set of track IDs.

Abstract: In one embodiment, a method of tracking multiple objects with a probabilistic hypothesis density filter is provided. The method includes obtaining measurements corresponding to a first object with at least one sensor, the at least one sensor providing one or more first track IDs for the measurements. A Tk+1 first predicted intensity is generated for the first object based on a Tk first track intensity. A Tk+1 measurement from a first sensor of the at least one sensors is obtained, the first sensor providing a second track ID for the Tk+1 measurement. The second track ID is compared to the one or more first track IDs, and the Tk+1 first predicted intensity is selectively updated with the Tk+1 measurement based on whether the second track ID matches any of the one or more first track IDs to generate a Tk+1 first measurement-to-track intensity for the first object.

Abstract: Systems and methods for inertial reference system alignment are provided. In certain embodiments, a system comprises an inertial reference system, the inertial reference system providing motion measurements; and a processing system coupled to receive the motion measurements from the inertial reference system. Further, the processing system is configured to execute instructions that direct the processing system to identify one or more frequencies in the spectrum of the motion measurements that are associated with vibrations; attenuate the motion measurements at the one or more frequencies; and use the attenuated measurements to aid in the production of navigation information.

Abstract: A system is provided for correlating evidence grids. In certain embodiments, the system includes a sensor that generates signals describing a current section of an environment; a memory configured to store measurements of historical sections of the environment; and a processor coupled to the sensor and configured to calculate navigation parameters based on signals received from the sensor. Further, the processor converts the signals received from the sensor into a current evidence grid and removes data from the current evidence grid to form a reduced evidence grid; converts the measurements of historical sections into a historical evidence grid; and correlates the reduced evidence grid with the historical evidence grid by adjusting position and orientation of the reduced evidence grid and the historical evidence grid in relation to one another and calculating correlative values, and searching for a highest correlative value.

Abstract: Systems and methods for a limb strike detector are provided. In certain embodiments, a system for detecting limb strikes comprises an inertial measurement unit (IMU) that provides inertial measurements; and a processing unit that receives the inertial measurements from the IMU.

Abstract: A method to filter outliers in an image-aided motion-estimation system is provided. The method includes selecting eight-image-points in a first image received from a moving imaging device at at least one processor; selecting eight-image-points in a second image that correspond to the selected eight-image-points in the first image at the at least one processor, the second image being received from the moving imaging device; scaling the selected image-points at the at least one processor so the components of the selected image-points are between two selected values on the order magnitude of 1; building an 8-by-9 matrix (A) from the scaled selected image-points at the at least one processor; determining a condition number for the 8-by-9 matrix at the at least one processor; and rejecting the 8-by-9 matrix built from the selected image-points when the determined condition number is greater than or equal to a condition-number threshold.

Abstract: Systems and methods for off-line and on-line sensor calibration are provided. In certain embodiments, a method for calibrating a sensor comprises receiving at least one reference measurement describing a system state for a system; and receiving at least one sensor measurement from the sensor, wherein the at least one sensor measurement is acquired from an observation of the environment of the system by the sensor. The method also comprises calculating a model residual power spectral density based on the at least one reference measurement and a sensor measurement model; and calculating a measurement residual power spectral density based on the at least one sensor measurement and the at least one reference measurement. Further, the method comprises identifying sensor parameters that morph the model residual power spectral density towards the measurement residual power spectral density.

Abstract: Systems and methods for a limb strike detector are provided. In certain embodiments, a system for detecting limb strikes comprises an inertial measurement unit (IMU) that provides inertial measurements; and a processing unit that receives the inertial measurements from the IMU.